| Literature DB >> 24358058 |
Reema Abu Khalaf1, Ghassan Abu Sheikha1, Mahmoud Al-Sha'er2, Mutasem Taha3.
Abstract
As incidence rate of type II diabetes mellitus continues to rise, there is a growing need to identify novel therapeutic agents with improved efficacy and reduced side effects. Dipeptidyl peptidase IV (DPP IV) is a multifunctional protein involved in many physiological processes. It deactivates the natural hypoglycemic incretin hormone effect. Inhibition of this enzyme increases endogenous incretin level, incretin activity and should restore glucose homeostasis in type II diabetic patients making it an attractive target for the development of new antidiabetic drugs. One of the interesting reported anti- DPP IV hits is Gemifloxacin which is used as a lead compound for the development of new DPP IV inhibitors. In the current work, design and synthesis of a series of N4-sulfonamido-succinamic, phthalamic, acrylic and benzoyl acetic acid derivatives was carried out. The synthesized compounds were evaluated for their in vitro anti-DPP IV activity. Some of them have shown reasonable bioactivity, where the most active one 17 was found to have an IC50 of 33.5 μM.Entities:
Keywords: Acrylic acid; DPP IV inhibitors; docking; pharmacophore modeling; phthalamic acid; succinamic acid; type II diabetes.
Year: 2013 PMID: 24358058 PMCID: PMC3866624 DOI: 10.2174/1874104501307010039
Source DB: PubMed Journal: Open Med Chem J ISSN: 1874-1045
The synthesized N4-sulfonamido-succinamic, phthalamic, acrylic and benzoyl acetic acid derivatives 6-21 with their fit values against Hypo32/8 and Hypo4/10, their QSAR-Estimated IC50 and in vitro DPP IV bioactivities
| Compound | Fit values against Hypo32/8 | Fit values against Hypo4/10 | QSAR estimated | ||
|---|---|---|---|---|---|
| 0 | 0 | 0.5535 | 3 ± 0.2 | - | |
| 0 | 0 | 0.0678 | 10 ± 0.5 | - | |
| 0 | 0 | 0.0069 | 5 ± 0.3 | - | |
| 0 | 0 | 0.1741 | 7 ± 0.7 | - | |
| 0 | 7.3231 | 0.0028 | 23 ± 0.8 | 54.4 | |
| 0 | 7.2859 | 0.0002 | 23 ± 0.3 | 43.2 | |
| 0 | 0 | 0.0281 | 22 ± 0.9 | 54.6 | |
| 0 | 0 | 0.0032 | 19 ± 1.5 | - | |
| 0 | 0 | 0.0002 | 15 ± 1.0 | - | |
| 0 | 0 | 0.0083 | 22 ± 1.1 | 59.3 | |
| 0 | 7.2859 | 0.0022 | 15 ± 1.1 | - | |
| 4.7265 | 0 | 20.200 | 25 ± 1.3 | 33.5 | |
| 4.7265 | 0 | 3.8253 | 17 ± 0.5 | - | |
| 0 | 0 | 0.6360 | 22 ± 0.9 | 48.5 | |
| 0 | 0 | 18.683 | 15 ± 1.1 | - | |
| 0 | 7.3076 | 0.6389 | 13 ± 0.4 | - | |
| 0 | 6.1005 | 0.0089 | 71 ± 1.0 | 2.7 |
Best-fit values against each binding hypothesis calculated by the equation [23]:
Fit = ∑ mapped hypothesis features x W [1-∑ (disp/tol) 2]
As calculated by QSAR equation (1) [17].
Percentage inhibition at 10 µM concentration.
Fit value of zero, means that the compound does not fit the hypothesis (misses a pharmacophoric feature).
IC50 values were determined from the corresponding dose-response lines at three concentrations with a correlation coefficient of 0.99.